Role of health workers and representative health worker organisations in LMIC pharmaceutical policy: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Health workers (HWs) and their representative health worker organisations (RHWOs) contribute to the design of pharmaceutical policy in low- and middle-income countries (LMICs), but their roles remain underappreciated. HWs and RHWOs can influence drug development, distribution, financing and access; however, which specific aspects HWs and RHWOs contribute to, and how they create change, remains insufficiently mapped within the global health literature. This protocol describes our process for conducting a scoping review to derive, describe, and classify existing literature on how HWs and RHWOs engage in pharmaceutical policy processes in LMICs. METHODS AND ANALYSIS: This review will follow the updated Arksey and O'Malley five-stage scoping review framework supported by iterations of methodological guidance and will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. We will search Ovid Medline, Ovid Embase and CAB Global Health for English-language peer-reviewed literature published between 2005 and 2025. Studies must discuss HW and RHWO involvement or influence in pharmaceutical policy or describe the roles, governance contexts or strategies of HWs or RHWOs in the context of pharmaceutical policy. Two reviewers will independently screen titles, abstracts and full texts using Covidence software to determine eligibility. We will chart data using Excel and summarise the findings thematically. We will consult stakeholders in the final stage of this review to provide feedback on the results of our review and guide our findings further in terms of actionable policy implications. ETHICS AND DISSEMINATION: Ethics approval is not required for this scoping review of published literature. Findings will be disseminated through peer-reviewed publications, academic presentations and policy engagement with global health actors. This review will inform future research and support evidence-informed pharmaceutical policymaking in LMICs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.181 | 0.135 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.019 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".